Department of Computational Medicine and Neuropsychiatry, Faculty of Medicine, University of Mons, Avenue du Champs de Mars 6, 7000 Mons, Belgium.
Psychiatr Danub. 2024 Sep;36(Suppl 2):342-347.
In child and adolescent psychiatry, the clinical presentation of disorders in adolescents is complex, and categorical approaches have limitations by focusing on individual disorders. The intricate system of psychopathology during adolescence can be effectively modeled using network science, which integrates statistical and computational techniques through artificial intelligence tools. Network analysis of psychometric data from psychiatric disorder assessment tests has been extensively studied in both general psychiatry and child psychiatry. However, a comprehensive evaluation of existing network approaches that model multiple psychiatric or neurodevelopmental disorders encountered in adolescents remains necessary. We conducted a systematic literature review across two different databases - PubMed and Scopus - using the keywords "network analysis", "adolescent" and "psychiatry" to address this question. The selection of articles was based on age criteria and the number of pathological entities studied. Out of 406 articles, 69 were selected and analyzed. The results from some of these studies are described in this article. Notably, we observe significant heterogeneity in the findings, highlighting both the richness and complexity of adolescent psychopathology. Further research is needed to validate the already proposed results and standardize the models studied.
在儿童和青少年精神病学中,青少年障碍的临床表现较为复杂,而通过关注个别障碍的分类方法存在局限性。使用网络科学可以有效地对青少年时期复杂的精神病理学系统进行建模,网络科学通过人工智能工具整合了统计和计算技术。在普通精神病学和儿童精神病学中,已经对来自精神障碍评估测试的心理计量数据的网络分析进行了广泛研究。然而,仍有必要对遇到的多种精神障碍或神经发育障碍进行建模的现有网络方法进行全面评估。我们在两个不同的数据库 - PubMed 和 Scopus - 中使用“网络分析”,“青少年”和“精神病学”这几个关键词进行了系统的文献回顾,以解决这个问题。根据年龄标准和研究的病理实体数量选择了文章。在 406 篇文章中,选择并分析了 69 篇。本文描述了其中一些研究的结果。值得注意的是,我们观察到结果存在显著的异质性,突出了青少年精神病理学的丰富性和复杂性。需要进一步的研究来验证已经提出的结果并标准化所研究的模型。